Static semantic analysis of dynamic languages

ABSTRACT

Analyzing dynamic source code. A method includes accessing a specific metadata format data structure. The data structure was created by obtaining one or more first data structures defining constructs in a body of dynamic language source code. From the one or more first data structures, identifier information is extracted for one or more of the defined constructs. Knowledge about the constructs is augmented. The metadata format data structure is parsed to compute metrics about the metadata format data structure. The metrics about the metadata format data structure are provided to a user.

BACKGROUND Background and Relevant Art

Computers and computing systems have affected nearly every aspect ofmodern living. Computers are generally involved in work, recreation,healthcare, transportation, entertainment, household management, etc.

Computers are typically controlled using computer software. The computersoftware includes executable instructions that can be executed by one ormore processors to cause the computer to perform various functions.Computer software may be created using source code created in aprogramming language. Code may categorized in several different ways.One distinctive method of categorizing computer code is categorizing itas either static or dynamic.

Static code can typically be easily analyzed before runtime as the codetypically is defined before runtime and does not change at runtime, thetype system is well defined before runtime and does not change atruntime, and types within the type system are defined before runtime anddo not change at runtime. Compilers, before runtime, can perform staticanalysis on static code and provide information to developers regardingcharacteristics of the static code or potential problems with a body ofcode.

Alternatively, some computer code may be classified as dynamic. Indynamic code, new code may be added at runtime. Additionally, staticcode type systems are not well defined before runtime. Further still,types within a static code type system can change at runtime. Thus,static analysis, before runtime, of dynamic code is hard due to thechanging nature of the dynamic code at runtime.

Dynamic languages such as JavaScript suffer from correctness issues thatare difficult to identify before runtime due to the dynamic nature ofthe languages. While static languages can more easily identifycorrectness issues in a compilation step, dynamic languages do not havethe same compilation step to identify such issues. Identifying theseissues at runtime is typically more costly than when editing orauthoring code. In some cases, diagnosing the root cause of a problem isextremely difficult due to, for example, non-obvious ways that symbolsare resolved at runtime.

The subject matter claimed herein is not limited to embodiments thatsolve any disadvantages or that operate only in environments such asthose described above. Rather, this background is only provided toillustrate one exemplary technology area where some embodimentsdescribed herein may be practiced.

BRIEF SUMMARY

One embodiment illustrated herein is directed to a method practiced in acomputing environment. The method includes acts for analyzing dynamicsource code. The method includes accessing a specific metadata formatdata structure. The data structure was created by obtaining one or morefirst data structures defining constructs in a body of dynamic languagesource code. From the one or more first data structures, identifierinformation is extracted for one or more of the defined constructs.Knowledge about the constructs is augmented. The metadata format datastructure is parsed to compute metrics about the metadata format datastructure. The metrics about the metadata format data structure areprovided to a user.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

Additional features and advantages will be set forth in the descriptionwhich follows, and in part will be obvious from the description, or maybe learned by the practice of the teachings herein. Features andadvantages of the invention may be realized and obtained by means of theinstruments and combinations particularly pointed out in the appendedclaims. Features of the present invention will become more fullyapparent from the following description and appended claims, or may belearned by the practice of the invention as set forth hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features can be obtained, a more particular descriptionof the subject matter briefly described above will be rendered byreference to specific embodiments which are illustrated in the appendeddrawings. Understanding that these drawings depict only typicalembodiments and are not therefore to be considered to be limiting inscope, embodiments will be described and explained with additionalspecificity and detail through the use of the accompanying drawings inwhich:

FIG. 1 illustrates transformation of a body of source code to anabstract syntax tree and use of the abstract syntax tree to create asymbol table;

FIG. 2 illustrates an example symbol table;

FIG. 3 illustrates another example symbol table;

FIG. 4 illustrates parsers used for parsing code into one or moreabstract syntax trees; and

FIG. 5 illustrates a method of creating metadata for dynamic code.

DETAILED DESCRIPTION

Some embodiments described herein may implement functionality to providesignificant useful semantic analysis of dynamic language source code bystatic means. In one illustrative example, this is accomplished byconstructing a symbol table, by declaration/annotation, inference,analysis and modeling of runtime behaviors, that provides informationthat would otherwise only be available at runtime during actual codeexecution. Metric analysis can be run against the symbol table and thisinformation. The metric analysis can provide important details regardingvarious issues related to the dynamic code including correctness issues,code organization issues, runtime execution issues, dependency analysisissues, etc. For example, in some embodiments, semantic checks may beperformed against the symbol table and information. The semantic checkscan identify important potential correctness issues and/or areas forcode improvement.

The following now illustrates details with regard to constructing asymbol table. Some embodiments illustrated herein implement an approachto generate and maintain symbolic references from source code, withoutliterally executing code, to support a range of features related toidentifying, analyzing, refactoring, etc, variables and definitions.

As intimated above, it is hard to conclusively identify symbols backingreferences in dynamic languages through static parsing and/or analysis.As a result, many modern editor language services today depend on codeexecution to generate a list of symbols at a specific source codecontext/scope. This approach has clear limitations and issues. It isdifficult to guarantee, for example, that a breakpoint set in aJavaScript function will be hit on calling it outside of actualprogram/web site execution (or that the breakpoint will be hit in atimely way). It is even less practical to consider executing code acrossan entire program to generate the comprehensive sort of symbol analysisthat would be performed to, for example, identify all code locationsthat reference a given symbol.

Thus, embodiments can address these issues by implementing an approachto generate and maintain symbolic references, without literallyexecuting code. In particular, as an alternate to code execution,embodiments may combine several components which, in concert, providesignificant symbol analysis outside of a runtime environment. The resultis a rich set of refactoring and other valuable integrated developmentenvironment features. An integrated development environment includes anintegrated application that provides development functionality such asediting, project management, source control, compilation and/or linking,publishing, post-build verifications, etc.

Referring now to FIG. 1, in some embodiments, a symbol table 102 isconstructed from implied and explicit inputs (such as, among otherthings, source files of a body of code 104) of a dynamic language. Asymbol table data structure correlates identifiers in a program's sourcecode with augmented information relating to its declaration orappearance in the source code. The symbol table may include, forexample, correlation between an identifier and information related totype, scope level, location, etc.

In some embodiments, symbols and symbol references are read frompersisted data and/or discovered and/or inferred from a multi-passtraversal of an abstract syntax tree (AST) representation 106 of a bodyof program code 104. While ASTs are referred to in the examples below,it should be appreciated that other types of syntax trees may be usedadditionally or alternatively. A symbol table 102 including mappingbetween source code offsets and symbolic references is constructed. Thismapping can be used to implement various editor features. For example,such features may include one or more of ‘go to symbol definition’,‘find all references to this symbol’, ‘rename this variable’, etc.

Illustrating now additional detail, some embodiments described hereininclude methods and/or apparatus to construct and understand a rich setof symbols & symbolic references, by combining several differenttechniques into a single system. For example, as illustrated in FIG. 1,a first technique uses one or more parsers 108 to create ASTs 106 fromsource code 104. The one or more parsers can construct symbol tables 102from the AST 106 input. A second technique that may be used, in someembodiments with the first technique, includes reading and/or hydratingstatic, literal descriptions of symbols directly. In particular, ifsymbols can be determined by static analysis or inferences, thistechnique could be used to resolve some symbols. A third technique thatcould be used with other techniques includes using type inferencing codethat models runtime type resolution. This could be augmented by staticannotations that signify type information and/or declarations forvariables. A fourth technique that could be used with other techniquesincludes using code and/or extensibility points that model symbol tablemanipulation based on an understanding of runtime behaviors of both aplatform itself and/or calls to specific APIs. A fifth technique thatcould be used with other techniques includes defining and/or enforcingcoding guidelines provided to developers that help maximizediscoverability of relevant information. In some embodiments, enforcingguidelines may be facilitated by using coding tools to drive enforcementof the coding guidelines.

FIGS. 2 & 3 illustrate example symbol tables raised from provided sourcecode. Referring now to FIG. 2, an example symbol mapping is illustratedfor the following code:

var g; function foo(p) { var v; }

The example demonstrates raising symbols from a variable declared atglobal scope (‘g’), a function ‘foo’ also declared at global scope, aparameter ‘p’ (the scope of which is constrained to function ‘foo’) anda local variable ‘v’, also constrained in scope to ‘foo’. Theillustration shows the hierarchical relationship of these symbols.Referring now to FIG. 3, an example symbol mapping is illustrated forthe following code

var g = { a: null, b: null }; function foo(p) { var v = { c: null }; }

Additional details are now illustrated. It should be appreciated thatwhile the following examples illustrate specific types, functions, etc.,other embodiments may use similar or equivalent types, functions, etc.In particular, naming strategies should not be considered limiting, butrather are used for concreteness and illustration. Illustrating nowfurther details, a first parser pass illustrating general AST 106 andhierarchical symbol table 102 construction is illustrated. In the firstpass, a set of inputs is identified, either explicitly (for example,using a command-line provided by a user or a program project filemaintained in an integrated development environment) or implicitly (forexample, by scanning product source code 104, making assumptions about aruntime execution environment, inferring dependencies from in-sourceinformation such as links to JavaScript, XML doc comments, etc).

Referring now to FIG. 4, a specific example of tools used to analyzeJavaScript applications are illustrated. While FIG. 4 illustrates aspecific JavaScript example, it should be appreciated that otherembodiments can use similar elements for other dynamic bodies of sourcecode. FIG. 4 illustrates two parsers, a format-capable parser 402 and aJavaScript parser 404. The parsers can parse various bodies of computercode to produce ASTs 406, such as the AST 106 illustrated in FIG. 1.

Embodiments can include source code which falls, in some examples, intoone of three categories: 1) product code, 2) other supporting‘framework’ code, and 3) other supporting ‘reference’ code, all of whichis represented by the body of source code 104 illustrated in FIG. 1. TheJavaScript parser 404 is able to parse product code or program sourcecode 408. Product code refers to the source code that comprises the usersource, which is typically the target of the analysis (ie, the sourcecode for which useful information or functionality is raised against).The JavaScript parser 404 may also parse supporting source code 410.Supporting source code 410 may include source code that facilitatesexecution of the program source code. For example, supporting sourcecode 410 may include framework source code. In general, supportingsource code may be code that is not part of a particular program, butthat can be used to provide more information about the program. Forexample, supporting source code may be one or more declarations oftypes. Supporting ‘framework’ code, refers to code that also executes atruntime but which is picked up from the system, other 3rd-parties, orwhich simply should not be regarded as of primary interest in thecurrent scenario. Supporting ‘reference’ code, refers to augmentinginformation which happens to be rendered in the format of the dynamiclanguage (because this is convenient, both for tooling and formaintenance by developers). ‘Reference’ code is consumed by the toolonly, it is not executed at runtime.

Input files may be read sequentially and abstract syntax trees 106created for them. The ASTs 406 are subsequently traversed and ahierarchical symbol table (such as the symbol table 102 illustrated inFIG. 1) is constructed from them that expresses scoping of alldiscovered symbols. Symbols for functions are constructed in this phase.

A pass subsequent to the first pass may be performed to accomplish typeinferencing and member population. During the subsequent pass, types areresolved as far as possible. In some embodiments, types may be resolved,for example, by inference and check. Also during the subsequent passmember symbols are populated. This subsequent pass is not performed insequential order. The following illustrates heuristics used to determinethe order in which the code is analyzed. Global code is analyzed first.Functions (both declarations and function expressions) are queued up forexecution, and ceteris paribus will be analyzed in the same order theywere found after all global code has been analyzed. A call to a functionwill cause it to be analyzed ad hoc, being removed from the queue, ifpresent, or added to it if not. When performing the latter step,‘Miranda’ prototyping rules are used, meaning that if the types of theparameters to a function are not known, they will be supplied by theknown types of the arguments at the first function call point.

In the following description, much of the descriptive information isspecific to JavaScript. However, it should be noted that these examplesare merely illustrative and other embodiments may be used with otherlanguages. Type inferencing is performed in a bottom-up fashion. As theparser 108 recursively walks the AST 106, it bubbles up types forsub-expressions recursively and applies rules to infer type expressionswhose type is unknown. The following illustrate rules that may beapplied. Literals (Boolean values, strings, numbers, null, objects,arrays) denote their own type. Identifiers that refer to functions areof type Function. Identifiers that refer to symbols whose types havebeen inferred are of the same type as the symbol to which they refer.Additive expressions are of type String if either operand is a String,in which case both sides are inferred to be of type String. Otheradditive expressions and all other arithmetic expressions (both binaryand unary) are of type Number, and their operands are inferred to be oftype Number. Boolean expressions (both binary and unary) are of typeBoolean, and their operands are inferred to be of type Boolean. Functioncall expressions are of the same type as the function being called hasbeen inferred to return. “New” expressions are of the type designated bythe function used in the new expression. Return statements cause thecurrent function to be inferred to return the type of the returnexpression. Control flow statements (for loops, ifs, switches, returns,etc.) are of type “void” (or “undefined” in JavaScript). For inferencerules above, it is possible to use annotations (see below) to explicitlydefine types.

In some embodiments, functions are categorized into one of fourcategories, i.e.: unknown, static functions, member functions, orconstructors. A function may be initially unknown and is categorizedbased on usage. A function called directly is considered static. Afunction called through on an object instance is the objects memberfunction. A function used in a new expression is marked as aconstructor. As with types, the annotations mechanism can also impactcategorization of functions.

Illustrating now a particular special case, JavaScript includes akeyword ‘this.’ The ‘this’ keyword refers to the execution context of afunction, which can differ for each function call. The resolution of‘this’ in JavaScript is dependent on runtime information complicatingperformance of a complete static analysis. Embodiments may use a numberof now illustrated heuristics to determine to what a reference to ‘this’refers. If the context is global code or if the function is static orunknown, then ‘this’ evaluates to a symbol that represents the globalscope (e.g., the “window” object in browsers). If the context is aconstructor, then ‘this’ evaluates to a prototype object of the functionit represents. If the context is a function being assigned to an objectmember, then ‘this’ evaluates to the object. If the context is a memberfunction, then ‘this’ evaluates to the prototype of the function thatdeclares the type of the member on which this function is being called.It is possible to use language augmentations (annotations) to describethe binding of the function and override the above heuristic rules.

For property accessors, the type of the left-hand side expression isevaluated and the right-hand side identifier is sought in the symboltable, following the relevant type's prototype chain.

Some embodiments may implement or support direct symbol hydration andsymbol hydration with alternate parsers. Embodiments may provide amechanism for directly populating the symbol table 102 based on parsinginputs other than literal source code that will execute at runtime. Inone illustrative example, the JavaScript parser 404 may further includefunctionality for parsing application programming interface (API) code.For example, FIG. 4 illustrates the JavaScript parser 404 parsing APIcode for W3C APIs, ECMA APIs, and browser-specific Document Object Model(DOM) APIs. W3C DOM API, ECMA(X) API (such as Math functions),JavaScript API, COM objects, browser-specific API, browser specific DOMextensions, etc, can be expressed as (generally bodiless) JavaScriptfunctions/variables that are passed to the AST analyzer described above.The JavaScript parser 404 may further include functionality for parsingreference code for other supporting JavaScript for which implementationis absent. This may be functionality (functions, types, etc.) that areassumed to be available during runtime, but are not part of the program.Reference code refers to metadata sufficient to model symbolicreferences which cannot be computed and/or inferred from productioncode. This may include the body of executable API that is provided asbuilt-in browser/ECMA script functionality (such as the HTMLElementclass and JS Math functions). This may include ‘foreign’ api that modelcode which is callable due to some interop mechanism (such as callinginto a COM object or a web service). Reference code may include ‘typedefinitions’ which are superimposed onto production code but which areotherwise irrelevant at runtime. In a reference file, for example,embodiments may include a description for a type that includes only twomethods, foo and bar. In a product file, a parameter may be annotated asbeing of this type. At analysis time, embodiments can ensure that onlymethods named foo or bar are called on that parameter.

The format-capable parser 402 is configured to parse HTML, COM typelibraries, and other descriptive formats as now described in moredetail. APIs that are ‘foreign’ to the language/runtime (i.e., for whichsome sort of special interop code is required to execute at runtime,e.g., COM objects) can be added to the symbol table by parsing relevantdescriptive formats (such as type libraries) and/or these descriptionscan be converted to a format (such as in the particular illustratedexample, JavaScript) which can be fed directly to the symbol tableconstruction code. The system can accept static (such asuser-authorable) descriptions of symbols as well as extensions thatparse arbitrary data formats and populate the symbol table accordingly.An example of the latter is an extension that parses HTML to populatethe symbol table with DOM elements expressed in mark-up that areaccessible to JavaScript code (such as calls to getElementsById). Thereis some tolerance in the system for errors and/or incompleteness ofreference data as distinct from production code (which will be modifiedand/or analyzed within the editor).

Some embodiments may implement or facilitate extensions that modelruntime symbol construction. Embodiments may provide a mechanism forpopulating the symbol table not merely with code as it is analyzed but,in some cases, based on the result at runtime when executing that code.Some useful examples relate to JavaScript utility code that constructsand populates object instances with members. Ecma5 JavaScript provideshelpers such as object.createProperty which can, in some cases, bemodeled by the system. String literals passed to eval can be parsed intoAST and injected into the AST and/or symbol table.

Some embodiments may benefit from constraining development practices tomaximize code discoverability. There are typically a set of codingguidelines/practices that have a high return as far as helping with theability of embodiments to function with a correspondingly low impact onthe expressiveness and/or utility of the dynamic language. One exampleof such a constraint is directing developers to avoid use of evalstatements in JavaScript. In some embodiments, these constraints may beenforced by coding tools which prevent developers from violatingconstraints, or at least warn a developer if they are about to break orexceed a constraint.

Embodiments may include a mechanism for reporting conditions to usersthat limit the ability to analyze source. In particular, there may arisesituations in which dynamic source code cannot be completely analyzedand/or all symbols resolved. Embodiments can include functionality toindicate such to developers when such conditions arise.

Using the symbol table, embodiments may implement a number of otherfunctionalities. For example, embodiments may implement various editorfeatures such as one or more of ‘go to symbol definition’, ‘find allreferences to this symbol’, ‘rename this variable and all references toit’, etc.

Embodiments may include functionality to create or use an ability todisplay a representation of implicitly available API, for informationalpurposes and to potentially serve as both the target for ‘go toreference’ or the source for ‘find all references to this symbol’features.

Embodiments may include functionality to create or use a mechanism formodeling symbol construction based on analyzed code. Embodiments mayinclude call sites to an API that constructs a class object based on aset of input parameters. For example, input parameters could betransformed into symbols that represent actual objects as they will beavailable at runtime, based on analyzed code.

Embodiments may include functionality to create or use a mechanism forspecifying, authoring/edited descriptive inputs representing symboltables entries, in formats such as XML, native JavaScript, etc. This mayalso include the ability to parse HTML to identify runtime-availableobjects. For example embodiments may be able to identify elements markedwith a specific identifier (such as an HTML ‘id’ attribute).

Embodiments may include functionality to create or use an ability toannotate source code with ‘type’ information. This may allow embodimentsto jump to a type or object definition that might exist as actualproject source or is solely represented in generated code and/or staticdescriptive input files.

Embodiments may include functionality to create or use an ability toannotate source code files with (or otherwise associate) a set ofdependencies (such as another supporting JavaScript file) used toconstruct a comprehensive symbol space for analysis.

The following discussion now refers to a number of methods and methodacts that may be performed. Although the method acts may be discussed ina certain order or illustrated in a flow chart as occurring in aparticular order, no particular ordering is required unless specificallystated, or required because an act is dependent on another act beingcompleted prior to the act being performed.

Referring now to FIG. 5, a method 500 is illustrated. The method 500 maybe practiced in a computing environment. The method 500 includes actsfor creating metadata for dynamic code in a descriptive metadatalanguage. The method includes obtaining one or more first datastructures defining constructs in a body of dynamic language source code(act 502). For example, in some embodiments, the one or more first datastructures comprise at least one of a syntax tree or an abstract syntaxtree. FIG. 1 illustrates a abstract syntax tree 106 derived, at least inpart from a body of source code 104. In the example illustrated in FIG.1, the abstract syntax tree 106 is the specific example of a datastructure.

The method 500 further includes, from the one or more first datastructures, extracting identifier information for one or more of thedefined constructs (act 504). For example, embodiments may extractsymbol names into a symbol table.

The method 500 further includes augmenting knowledge about theconstructs (act 506). Augmenting knowledge about the constructs can beaccomplished in a number of different ways. For example, augmenting maybe based on explicit inspection of the body of dynamic language sourcecode. For example, the dynamic language source code may include commentsin the code that can be used to augment knowledge about constructs inthe code. Explicit inspection of the body of dynamic language sourcecode may include inspection of code that is a surrogate for an actualimplementation or which models code that is not explicitly expressed insource code form. For example, this may include cases of dropping inreference files to replace 3rd party frameworks in an analysis toolchain as well as modeling things like built-in DOM API (which have noactual representation as JavaScript source code.

Alternatively or additionally, augmenting may be based on one or moreimplied inferences. For example, if it can be determined that sourcecode concatenates to a string literal using an object as an operand, itcan be determined that the resulting object is a string. If anarithmetic operation is performed using an object as an operand, it canbe determined that the object is a numerical type, such as an integer orfloating point. Inferences may be may be made based on a frameworksupporting source code. For example, knowledge about a framework andknowing how that framework will consume source code can facilitateinferring addition information about the source code. Similarly, contextcan be used to infer additional information. For example, context suchas a browser which source code will be used with and knowing how thatbrowser will interact with source code can facilitate inferring additioninformation about the source code. Further still, stand in code can beused to make inferences to augment knowledge about source code. Stand-incode provides an alternate body (that is, implementation) of a functionthat is expressly designed to assist in computing symbolic informationfor variables that are within scope (as opposed to being intended toexecute at runtime). This is an alternate approach to analyzing theactual implementation of a function to acquire information or dependingstrictly on annotations.

Embodiments could be implemented that include augmentation as a resultof folding in runtime collected data. In particular, embodiments mayinstrument the runtime to provide information about how the type of setof types that a parameter resolved to at a specific code location. Thisnew information may be folded into the augmented information.

Embodiments could be implemented that include augmentation as a resultof modeling the results of executing code. For example, embodiments ofthe method 500 may be performed where augmenting includes modeling theeffects upon a symbol table that would result from executing a call toone or more functions based on explicit, inferred or computed call sitedetails. For example, assume that an embodiment has knowledge of afunction constructNamespace(namespaceName), which creates a globalobject of the name that is passed in as an argument. During analysis,when embodiments observe a call site constructNamespace(“My.Namespace”),the tool could add the specified namespace object to the symbol table sothat it is subsequently available when processing the remainder of thefunction. Other embodiments may implement a more complicated pathanalysis to calculate a number of possible paths through the function,with implied arguments provided to a callee. For example, embodimentsmay implement symbolic execution, abstraction interpretation, controland data flow analysis, etc.

Alternatively or additionally, augmenting may be based on user input.For example a user interface using a command line tool and/or graphicalbased tool may be used to augment the body of dynamic language sourcecode. For example, a user can provide additional information aboutobjects in code, similar to how commenting might work, but withoutneeding to formally comment the source code. Rather, the tool may beused to allow a user to make external comments about source code.

The method 500 further includes providing metadata about the body of thedynamic language source code with the source code in a specific metadataformat to a user (act 508). For example, and as illustrated previously,the specific metadata format may include a symbol table.

The following now illustrates semantic static analysis that can beimplemented in some embodiments.

Embodiments may alternatively or additionally include parsing themetadata format data structure to compute metrics about the metadataformat data structure and providing the metrics about the metadataformat data structure to a user.

In some embodiments, the metrics may provide code correctness analysis.For example, calls to functions which cannot be resolved to a symbol(indicating a possible typographical error and/or runtime failure tobind to an existing function) may be detected and indicated.

For example, the correctness analysis may indicate the existence ofduplicate local members in a construct. For example, duplicate variabledefinitions within a function body may be detected and indicated.

Alternatively or additionally, the correctness analysis indicates theexistence of duplicate members in an object. This may include theexistence of duplicate members in a global space.

Alternatively or additionally, the correctness analysis indicates theexistence of duplicate cases in a switch block or conditional statement.For example, an if-then-else block may include duplicate cases. This canbe detected by codepath analysis against the symbol table, and indicatedto a user.

Alternatively or additionally, the correctness analysis indicates issuesrelated to contextual use of certain expressions. For example,embodiments may indicate the presence of return statements in globalcode. In other embodiments, the correctness analysis might assume aspecific runtime environment such as one or more browser families (suchas Microsoft Internet Explorer), browser versions, browser executionmodes (such as ECMA ‘strict’ mode) and alter results accordingly.

Alternatively or additionally, the correctness analysis indicates scopeclobbering for local symbols. This may be particularly useful in dynamiclanguages where typographical errors, and such do not result in compileand/or link-time errors.

Alternatively or additionally, the correctness analysis indicates typeconflicts discovered during a type inferencing phase as errors. Inparticular, errors can be indicated when an expression has a differenttype than what it is inferred and/or annotated to have.

Alternatively or additionally, the correctness analysis indicatesparameter count mismatches.

Alternatively or additionally, the correctness analysis identifiesunreachable code. In particular the codepath analysis against the symboltable may be able to help pinpoint when code is not reachable from othercode in a source code body. For example, embodiments may indicateconditional clauses that evaluate to a constant condition, therebyrendering some portion of the conditional statement unreachable.

Alternatively or additionally, the correctness analysis indicates returntype mismatches across different code paths. In particular, for bestreliability, it is helpful for functions to return objects of aconsistent type. The symbol table can be used to identify return ofinconsistent types from a function. Exceptions can be regarded as a kindof return type as well and additional embodiments might factor exceptionraising behavior into the correctness analysis.

Alternatively or additionally, the correctness analysis indicates returncompleteness issues. In particular, the symbol table can be used todetermine all codepaths returning values and those not returning values.

Alternatively or additionally, the correctness analysis indicatesfailure to explicitly declare variables before use. Requiring developersto explicitly provide the ‘liar’ keyword when declaring variables inJavaScript does not significantly increase cost of development and haslittle to no impact on language expressiveness. With this standard inplace, an analysis that flags implicit variable declarations flags typosand/or correctness problems in code. Due to JavaScript's scoping rules,an undeclared variable that appears within one function will be declaredat global scope, making it viewable to all. This can be the source ofextremely subtle and hard-to-debug runtime issues, particularly if avariable of the same name that was intended to be local in a separatefunction was also specified without the ‘liar’ keyword. Thus, theseissues can be discovered using the symbol table and indicated to a user.

Alternatively or additionally, the correctness analysis indicatesunexpected line terminations and/or dependence on virtual semicolons.

Alternatively or additionally, the correctness analysisopportunistically provides early discovery of syntax and/or parsingerrors.

In some embodiments, the metrics may provide code organization analysis.

For example, the code organization analysis may be related to closuredetection. A closure is the local variables for a function kept aliveafter the function has returned, or a closure is a stack-frame which isnot deallocated when the function returns. A closure is formed when oneof those inner functions is made accessible outside of the function inwhich it was contained, so that it may be executed after the outerfunction has returned. Embodiments may include functionality to detectclosures.

Alternatively or additionally, the metrics provide code runtimeexecution analysis. In some embodiments, for example, the symbol tablemight be manipulated during analysis in order to model runtime codeexecution.

Alternatively or additionally, the metrics provide code dependencyanalysis.

Embodiments may include functionality for performing a directed query ofthe metrics. For example, embodiments may identify all places calls to aspecific function are made.

Embodiments may further include accessing a plurality of metadata datastructures and performing a delta analysis on the data structures todetermine differences in bodies of source code. Thus, some embodimentsmay compare two different symbol tables to determine the differencesbetween the symbol tables and thus the bodies of source code.

Embodiments may be implemented where the metrics are embedded into thespecific metadata format data structure. For example, a symbol table mayinclude some of the metrics described herein embedded in the symboltable itself.

Illustrating now a specific example, consider the following source code:

/// <dictionary target= ‘all’> /// eval, obj /// <dictionary>/// <disable>JS2076, JS3056</disable> <setting key=‘JS2058.DoNotUseIncrementAndDecrementOperators.Strict’>true</setting>function consumesMyClass(/* @type(MyClass) */myClass) { var myField =myClass.instanceField myClass.instanceMember(10) var myClassBaseField =myClass.baseField; myClass.baseMember(1, 2, 3); };

This code is now used to demonstrate various in-source mechanisms forconfiguring analysis, augmenting symbol construction, and managingresults. The first annotations are expressed as in-source XML documentcomments and represent, in order, a dictionary that is used whenspellchecking code identifiers, a comment that disables analysis forchecks labeled as JS2076 and JS3056 (or suppresses reporting of resultsfor these checks), and a setting that configures the analysis of anothercheck, JS2058, in order to put it in a strict reporting mode.

The code example further illustrates an inlined C-style comment thatspecifies the type, ‘MyClass’ for a parameter of a function. Thedefinition of MyClass could be specified by annotation elsewhere in thecode, or the symbol might be constructed during a pass by code thatmodels the result of runtime calls, creates symbols for ‘foreign’ apisuch as COM objects/other interop models, etc.

Further, the methods may be practiced by a computer system including oneor more processors and computer readable media such as computer memory.In particular, the computer memory may store computer executableinstructions that when executed by one or more processors cause variousfunctions to be performed, such as the acts recited in the embodiments.

Embodiments of the present invention may comprise or utilize a specialpurpose or general-purpose computer including computer hardware, asdiscussed in greater detail below. Embodiments within the scope of thepresent invention also include physical and other computer-readablemedia for carrying or storing computer-executable instructions and/ordata structures. Such computer-readable media can be any available mediathat can be accessed by a general purpose or special purpose computersystem. Computer-readable media that store computer-executableinstructions are physical storage media. Computer-readable media thatcarry computer-executable instructions are transmission media. Thus, byway of example, and not limitation, embodiments of the invention cancomprise at least two distinctly different kinds of computer-readablemedia: physical computer readable storage media and transmissioncomputer readable media.

Physical computer readable storage media includes RAM, ROM, EEPROM,CD-ROM or other optical disk storage (such as CDs, DVDs, etc), magneticdisk storage or other magnetic storage devices, or any other mediumwhich can be used to store desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer.

A “network” is defined as one or more data links that enable thetransport of electronic data between computer systems and/or modulesand/or other electronic devices. When information is transferred orprovided over a network or another communications connection (eitherhardwired, wireless, or a combination of hardwired or wireless) to acomputer, the computer properly views the connection as a transmissionmedium. Transmissions media can include a network and/or data linkswhich can be used to carry or desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer. Combinationsof the above are also included within the scope of computer-readablemedia.

Further, upon reaching various computer system components, program codemeans in the form of computer-executable instructions or data structurescan be transferred automatically from transmission computer readablemedia to physical computer readable storage media (or vice versa). Forexample, computer-executable instructions or data structures receivedover a network or data link can be buffered in RAM within a networkinterface module (e.g., a “NIC”), and then eventually transferred tocomputer system RAM and/or to less volatile computer readable physicalstorage media at a computer system. Thus, computer readable physicalstorage media can be included in computer system components that also(or even primarily) utilize transmission media.

Computer-executable instructions comprise, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. The computer executable instructions may be, forexample, binaries, intermediate format instructions such as assemblylanguage, or even source code. Although the subject matter has beendescribed in language specific to structural features and/ormethodological acts, it is to be understood that the subject matterdefined in the appended claims is not necessarily limited to thedescribed features or acts described above. Rather, the describedfeatures and acts are disclosed as example forms of implementing theclaims.

Those skilled in the art will appreciate that the invention may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, mobile telephones,PDAs, pagers, routers, switches, and the like. The invention may also bepracticed in distributed system environments where local and remotecomputer systems, which are linked (either by hardwired data links,wireless data links, or by a combination of hardwired and wireless datalinks) through a network, both perform tasks. In a distributed systemenvironment, program modules may be located in both local and remotememory storage devices.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or characteristics. The described embodimentsare to be considered in all respects only as illustrative and notrestrictive. The scope of the invention is, therefore, indicated by theappended claims rather than by the foregoing description. All changeswhich come within the meaning and range of equivalency of the claims areto be embraced within their scope.

1. In a computing environment, a method of analyzing dynamic sourcecode, the method comprising: accessing a specific metadata format datastructure wherein the data structure was created by obtaining one ormore first data structures defining constructs in a body of dynamiclanguage source code; from the one or more first data structures,extracting identifier information for one or more of the definedconstructs; augmenting knowledge about the constructs; parsing themetadata format data structure to compute metrics about the metadataformat data structure; and providing the metrics about the metadataformat data structure to a user.
 2. The method of claim 1, wherein themetrics provide code correctness analysis.
 3. The method of claim 2,wherein the correctness analysis indicates the existence of duplicatelocal members in a construct.
 4. The method of claim 2, wherein thecorrectness analysis indicates the existence of duplicate members in anobject or type.
 5. The method of claim 2, wherein the correctnessanalysis indicates the existence of duplicate cases in a switch block.6. The method of claim 2, wherein the correctness analysis indicatesissues related to contextual use of certain expressions.
 7. The methodof claim 2, wherein the correctness analysis indicates scope clobberingfor local symbols.
 8. The method of claim 2, wherein the correctnessanalysis indicates type conflicts discovered during a type inferencingphase as errors.
 9. The method of claim 2, wherein the correctnessanalysis indicates parameter count mismatches.
 10. The method of claim2, wherein the correctness analysis identifies unreachable code.
 11. Themethod of claim 2, wherein the correctness analysis indicates returntype mismatches across different code paths.
 12. The method of claim 2,wherein the correctness analysis indicates return completeness issues byindicating at least one of codepaths returning values or codepaths notreturning values.
 13. The method of claim 2, wherein the correctnessanalysis indicates failure to explicitly declare variables before use.14. The method of claim 2, wherein the correctness analysis indicatesunexpected line terminations.
 15. The method of claim 2, wherein thecorrectness analysis opportunistically provides early discovery ofsyntax/parsing errors.
 16. The method of claim 1, further comprisingperforming a directed query of the metrics.
 17. The method of claim 1,wherein the metrics are embedded into the specific metadata format datastructure.
 18. The method of claim 1, further comprising accessingsecond data structure and performing a delta analysis.
 19. One or morecomputer readable media comprising computer executable instructions thatwhen executed by one or more processors cause one or more processors toperform the following: accessing a specific metadata format datastructure wherein the data structure was created by obtaining one ormore first data structures defining constructs in a body of dynamiclanguage source code; from the one or more first data structures,extracting identifier information for one or more of the definedconstructs; augmenting knowledge about the constructs; parsing themetadata format data structure to compute metrics about the metadataformat data structure; and providing the metrics about the metadataformat data structure to a user.
 20. In a computing environment, asystem for analyzing dynamic code, the system comprising: one or moreprocessors; one or more computer readable media coupled to the one ormore processors, wherein the one or more computer readable mediacomprise computer executable instruction that when executed by one ormore of the one or more processors cause one or more of the one or moreprocessors to perform the following: parsing source code to generate oneor more syntax trees defining constructs in a body of dynamic languagesource code; from the one or more syntax trees, extracting identifierinformation for one or more of the defined constructs; augmentingknowledge about the constructs by at least one of explicit inspection ofthe body of source code or implied references related to the sourcecode; producing a correlation between identifiers and augmentedknowledge; using the identifier information and augmented knowledge,generating metadata about the body of the dynamic language source code,the generated metadata being represented as a symbol table; andproviding the metrics about the metadata format data structure to auser.